# You can write R code here and then click "Run" to run it on our platform

library(readr)

# The competition datafiles are in the directory ../input
# Read competition data files:
train <- read_csv("../input/train.csv")
test <- read_csv("../input/test.csv")



# Generate output files with write_csv(), plot() or ggplot()
# Any files you write to the current directory get shown as outputs
# You can write R code here and then click "Run" to run it on our platform


library(caret)
inTrain<-createDataPartition(train$label,p=0.25,list=F)
train.in<-train[inTrain,]
label<-factor(train.in$label)
train.in$label<-NULL
train.in<-round(train.in/255.0,3)

# Write to the log:
cat(sprintf("Training set has %d rows and %d columns\n", nrow(train), ncol(train)))
cat(sprintf("Test set has %d rows and %d columns\n", nrow(test), ncol(test)))

library(kernlab)
ctrl<-trainControl(method='cv',number=10)
fit.svm<-train(label~.,data=train.in,method='svmLinear',trControl=ctrl)
print(fit.svm)
rslt<-predict(fit.svm,test,type='raw')
predictions <- data.frame(ImageId=1:nrow(test), Label=rslt)
write_csv(predictions,'submission.csv')